Melissa Data Quality vs WinPure Data Quality Platform comparison

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Melissa Logo
619 views|343 comparisons
95% willing to recommend
WinPure Logo
0 views|0 comparisons
0% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Melissa Data Quality and WinPure Data Quality Platform based on real PeerSpot user reviews.

Find out what your peers are saying about Informatica, SAP, Talend and others in Data Quality.
To learn more, read our detailed Data Quality Report (Updated: June 2024).
772,649 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"​We are able to more accurately identify valid, and better formatted, data which improves the data we store in our database.​""We use a Melissa API to access the data, so it easy to use, accurate, and fast.""​It has a straightforward, easy setup.""Provides quality accurate data that our downstream solutions depend on.""​Allows us to identify cell phones before dialing, and giving us data about callers.""We use their GeoPoints to get the most precise, rooftop level geocoding.""Be confident that the scalability and load are not going to be an issue with the services. ​""Provides simplicity, ease of use, combined with overall accuracy of data."

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"With regards to choosing flash versus traditional storage, it's just so much simpler to manage and users get so much better performance from flash."

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Cons
"It will mix up family members at times, so we will change addresses at times that shouldn’t be changed.""We are no longer using Melissa Data to clean up our address information as there are free tools that we can use to do the same thing.""It would be helpful if a list of the codes and explanations could be included.""The custom software solution we still use in-house makes Excel a lot slower than usual.""We would appreciate it if there was a larger database so that we could find information more often. For example, we can search for 10 people and only find the information for three of them, if we are lucky.""Speed of delivery/ease of use. They advertise a 24-hour, next business day turn time on data annotation, but I’ve found it is usually closer to 72 hours. This is still excellent, just make sure you add in the appropriate fluff to your delivery timelines.""MatchUp is a more complex product and I recommend a test area before upgrading to production. Performance can change from version to version.""​If I had multiple Excel files open and ran Listware it would crash Excel, charge the credits, and not save the results."

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"The pricing model could use improvement."

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Pricing and Cost Advice
  • "It's affordable."
  • "The price for address validation is similar in all software. However, the price for geocoding decides the actual pricing. If you get their most accurate geocoding (called GeoPoints), then it will add about $10k+ per million requests."
  • "They were willing to work with our preferred vendors, though it involved extra steps to get the license."
  • "Depends on situation. We prefer to have data onsite, but some might prefer web access."
  • "Melissa pricing is competitive."
  • "Pricing is very reasonable."
  • "I think it's worth the value for me to run it."
  • "Generally, the cost is ROI positive, depending on your shipping volume."
  • More Melissa Data Quality Pricing and Cost Advice →

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    Ranking
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    343
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    WinPure
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    Overview

    Data Quality Components for SSIS

    This suite of data transformations for Microsoft SQL Server Integration Services (SSIS) delivers the full spectrum of data quality including data profiling, data verification, data enrichment and data matching. With an intuitive interface and drag/drop capabilities, this powerful toolkit makes it easy to unify data into a single version of the truth for Master Data Management (MDM) success.

    Winpure Data Cleaning Matrix provides a method of applying a whole host of cleaning processes onto your data. Containing an array of tools to help clean, correct, standardize and transform your data the matrix is divided into 7 sections, each section focusing on a specific data cleaning operation. All settings can then be stored and used on other similar data sets thus saving a lot of time.

    Sample Customers
    Boeing Co., FedEx, Ford Motor Co, Hewlett Packard, Meade-Johnson, Microsoft, Panasonic, Proctor & Gamble, SAAB Cars USA, Sony, Walt Disney, Weight Watchers, and Intel.
    Birmingham Hippodrome, Luton Borough Council, Apex Innovations, Sandia National Laboratories, Clear Blue, Vodafone
    Top Industries
    REVIEWERS
    Healthcare Company16%
    Retailer11%
    Financial Services Firm11%
    Government11%
    VISITORS READING REVIEWS
    Manufacturing Company13%
    Computer Software Company12%
    Financial Services Firm11%
    Government10%
    No Data Available
    Company Size
    REVIEWERS
    Small Business41%
    Midsize Enterprise10%
    Large Enterprise48%
    VISITORS READING REVIEWS
    Small Business24%
    Midsize Enterprise17%
    Large Enterprise58%
    No Data Available
    Buyer's Guide
    Data Quality
    June 2024
    Find out what your peers are saying about Informatica, SAP, Talend and others in Data Quality. Updated: June 2024.
    772,649 professionals have used our research since 2012.

    Melissa Data Quality is ranked 9th in Data Quality with 40 reviews while WinPure Data Quality Platform is ranked 24th in Master Data Management (MDM) Software. Melissa Data Quality is rated 8.4, while WinPure Data Quality Platform is rated 0.0. The top reviewer of Melissa Data Quality writes "SSIS MatchUp Component is Amazing". On the other hand, the top reviewer of WinPure Data Quality Platform writes "A solution that offers good performance, good stability, and a straightforward setup". Melissa Data Quality is most compared with Informatica Address Verification, SAP Data Quality Management, Precisely Trillium and Experian Data Quality, whereas WinPure Data Quality Platform is most compared with .

    We monitor all Data Quality reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.